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					The Golden Horn in Istanbul




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Abstract

The Golden Horn, or Haliç in Turkish, is a horn-shaped fiord on the European side of Istanbul
and is fed by two small streams.It is a natural harbor where Byzantine and Ottoman fleet
and commercial ships were anchored. Today, it's surrounded by parks and promenades with
ancient sites around it. Its name comes from the color of the water when at sunset it shines
with a gold color because of the reflection of the sun.

Golden Horn was an old trading harbor and a popular residential area during the Byzantine
period. Its entrance was blocked by a huge chain to stop unwanted ships to enter. During the
Ottoman period it was largely inhabited by Jewish immigrants from Spain. The mixtures of
Armenians, Greeks, Gypsies and Turks living along its shores reflected the city's colorful
ethnic mosaic.
                                                                                            3
In the first half of 18th century the Golden Horn was famous for its tulip gardens where
upscale people came to enjoy and row with their boats at the romantic sunset.

With the population explosion in the 1950's and ineffective building laws, the Golden Horn
became an ugly storage of grey city-sewage and industrial waste with a terrible odor. But in
the 1980's an urban clean-up began, clearing up these factories and building proper sewage
systems around the Golden Horn. Now, its shores are green once again with parks,
promenades, and playgrounds. There is still lots to do but at least now people don't have to
change their course because of the bad odor, and they can even fish there.

Fener and Balat are old neighborhoods of the Golden Horn, with traditional old wooden
houses, Byzantine churches, and a couple of old synagogues belonging to the first Jewish”
community who was settled here. The Orthodox Patriarchy resides here as well.




                             Hope to see you soon in Istanbul.
   1. Introduction

Estuaries are transition zones from the freshwater to the sea, supporting a diverse range of
biota and serving as habitat,breeding grounds or nursery areas for many species (Ketchum,
1983). Conditions in estuaries are highly variable.As a result of rainfall, overland runoff and
meteorological conditions salinity fluctuates in a wider range. In addition, anthropogenic
effects are stronger at the estuaries since water circulation is much more limited than the
coastal ecosystem.
The Golden Horn has long been important to the civilizations of Istanbul, and its ecosystem
faced pollution over centuries. Documents show that the regulations concerning the control
of pollution around Golden Horn date back to the Byzantine period. Sultan Mehmet the
Conqueror prepared a decree to prevent the filling and pollution of the estuary in the 1450s
(Erog˘lu et al., 2001). On the other hand, the turning point for the Golden Horn was 1950s.
The increase in settlements and industrial facilities around the Golden Horn since the 1950s
caused severe pollution,particularly from wastewaters of pharmaceutical, detergent,dye and
leather industries and domestic discharges. The7.5 km long, 900 m (max) wide estuary,
located at the South west of the Strait of Istanbul, was originally characterized by a two-
layered structure similar to the neighboring Strait of Istanbul.The estuary received
feshwater from two streams discharging to the uppermost part. Following the construction
of a series of dams on these streams, freshwater influx considerably decreased and rain
and coastal inputs became the main sources of freshwater in the Golden Horn (Sur et al.,
2002). The maximum depth vof the estuary was around 40 m at the lower parts while the
depth rapidly decreases to 15 m in mid-estuary and to 4–5 min the upper parts. However as
a consequence of estuarine characteristics and anthropogenic impacts, a major proportion
of the estuary was almost completely filled with sediment and upper parts have been
connected to the middle estuary only through a narrow channel since the early 1990s.
The devastation of Golden Horn had drastically affected its ecosystem.Severe pollution
limited aquatic life to the surrounding of Galata Bridge, while more upper parts were almost
lifeless (Gu¨vengiris_, 1977).Within the framework of rehabilitation studies started in

                                                                                               4
1990, an important part of the surface discharges were gradually taken under control and
connected to collector systems.
The industrial facilities and buildings at the coasts of the estuary were expropriated
and flattened. The shipyard facilities were limited and the dry docks were moved out from
the estuary to enhance upper layer circulation.
The response of the Golden Horn ecosystem to the latest achievements in rehabilitation
efforts was very quick and diversified. (e.g. Tuncer et al., 2001; Altunkaynak
et al., 2005).




Materials and methods




                                                                                            5
We studied with 3 different stations.

1.Station-410 02’ 27,48”K 280 56’46,05”D


2.Station-410 01’ 56,06”K 280 57’16,94”D


3.Station-410 01’ 16,75”K 280 58’05,20”D


Sampling:


Samples were collected in November using a Van Veen grab from different depths(5-30m).
The Van Veen grab is used to take sediment samples from the sea floor.




The grab is lowered to the sea bed on a steel cable with its "jaws" open. As soon as the
dishes touch the bottom, the valve keeping them open is released. As the grab is pulled back
up the jaws close, scooping up sand or sediment from the seabed. The grab is opened over a
sloping table on the ship and the contents are collected in a plastic bag to study

                                                                                           6
macrobenthic communities and retained materials fixed in %4 formaldehyde for the
preservation of biological specimens.




The collected samples were separated from the sediment using a 0.5 mm sieve and retained
materials fixed in %4 formaldehyde for preservation of biological specimens.

 After ten days benthic samples were rinsed with tap water. By using labaratory tray we
seperated the species.Then we put bentic organisms in bottles which contains %70 alcohol
to identify the species for classification.

The plankton was sampled from this 3 different stations and depths for qualitative purpose .




Water layer was assayed with a plankton scoop-net(mesh size 40micrometer).To classify this
phytoplancton species we are using Olympus CK2 model phase contrast microscope.
Seawater was collected by using nansen bottles .


                                                                                           7
It was enclosed in a protective cage that contained a 2.5 L Niskin bottle, which were closed
by sending a messenger down the line in order to collect samples at varying depths in the
water column. Samples were collected in 100 mL polyethylene (LDPE) bottles, 250mL
plankton bottles.For bentic organisms we used 3L bottles.




Sample nutrients was protected under -200 C before analysis.

Physicochemical variables:

Temperature- The sea temperature at the water sampling depth is recorded by means of a
reversing thermometer fixed to the Nansen bottle.


Transparency

Transparency was measured with a Secchi disc at sampling time The Secchi disk was 8-inches in
diameter with alternating black and white quadrants. This instrument is used to measure light
attenuation in surface water. The disk is lowered on a line in ½ meter increments to the depth at
which it disappears from view. When the disk is no longer visible to the human eye, the depth was
recorded. Measurements were taken at each of the sampling stations. All of the surface
measurements were collected off the side of the research vessel with consistent light.




Dissolved oxygen:




                                                                                                    8
Replicate samples were taken at each sampling station, two of which were collected at
depth and two at the surface. The samples were collected in pre-measured flasks that were
sealed with a stopper. Water was drawn from the Niskin bottle through a rubber hose to
prevent exposure to atmospheric oxygen. Once filled, the flasks were injected with 1 ml of
manganous chloride and 1 ml of alkaline sodium iodide reagents. The stopper was placed in
the flask, its contents shaken and stored in the dark for transport to the laboratory. At the
lab, the remaining steps of the Winkler Titration Method were performed using a Dosimat
automatic titrator . Once a standard was established, the samples were titrated as follows:
add stir bar to flask with collected sample, add 1 ml of sulfuric acid, place bottle on stirrer,
titrate sample by adding thiosulfate, when the sample turns a straw yellow in color add 1 ml
of starch and titrate to endpoint which is when the sample became clear.

ACKNOWLEDGEMENT
Biological Oxygen Demand (BOD) – Overview
Author Unknown
Biochemical Oxygen Demand (BOD) refers to the amount of oxygen that would be
consumed if all the organics in one liter of water were oxidized by bacteria and protozoa
(ReVelle and ReVelle, 1988).
The first step in measuring BOD is to obtain equal volumes of water from the area to be
tested and dilute each specimen with a known volume of distilled water which has been
thoroughly shaken to insure oxygen saturation.
After this, an oxygen meter is used to determine the concentration of oxygen within one of
the vials. The remaining vial is than sealed and placed in darkness and tested five days later.
BOD is then determined by subtracting the second meter reading from the first.
The range of possible readings can vary considerably: water from an exceptionally clear lake
might show a BOD of less than 2 ml/L of water. Raw sewage may give readings in the
hundreds and food processing wastes may be in the thousands.


Background Information
Microorganisms such as bacteria are responsible for decomposing organic waste. When
organic matter such as dead plants, leaves, grass clippings, manure, sewage, or even food
waste is present in a water supply, the bacteria will begin the process of breaking down this

                                                                                                9
waste. When this happens, much of the available dissolved oxygen is consumed by aerobic
bacteria, robbing other aquatic organisms of the oxygen they need to live.
Biological Oxygen Demand (BOD) is a measure of the oxygen used by microorganisms to
decompose this waste. If there is a large quantity of organic waste in the water supply, there
will also be a lot of bacteria present working to decompose this waste. In this case,the
demand for oxygen will be high (due to all the bacteria) so the BOD level will be high. As the
waste is consumed or dispersed through the water, BOD levels will begin to
decline.
Nitrates and phosphates in a body of water can contribute to high BOD levels. Nitrates and
phosphates are plant nutrients and can cause plant life and algae to grow quickly.
When plants grow quickly, they also die quickly. This contributes to the organic waste in the
water, which is then decomposed by bacteria. This results in a high BOD level.
When BOD levels are high, dissolved oxygen (DO) levels decrease because the oxygen that is
available in the water is being consumed by the bacteria. Since less dissolved oxygen is
available in the water, fish and other aquatic organisms may not survive.

BOD Level (in ppm)                             Water Quality
1-2                                            Very Good
                                               There will not be much organic waste
                                               present in the water supply.

3-5                                            Fair: Moderately Clean
6-9                                            Poor: Somewhat Polluted
                                               Usually indicates organic matter is present
                                               and bacteria are decomposing
                                               this waste.

100 or greater                                 Very Poor: Very Polluted
                                               Contains organic waste.



NOTE: Generally, when BOD levels are high, there is a decline in DO levels. This is
because the demand for oxygen by the bacteria is high and they are taking that oxygen from
the oxygen dissolved in the water. If there is no organic waste present in the water, there
won't be as many bacteria present to decompose it and thus the BOD will tend to be lower
and the DO level will tend to be higher.
At high BOD levels, organisms such as macro invertebrates that are more tolerant of
lower dissolved oxygen (i.e. leeches and sludge worms) may appear and become
numerous. Organisms that need higher oxygen levels (i.e. caddisfly larvae and mayfly
nymphs) will NOT survive.


Suspended solids

Suspended solids analysis performed gravimetrically by using 2540-D method .


                                                                                             10
Salinty- We used Mohr-Knudsen Titration for the Chlorinity of Sea Water.

pH,conductivity

YSI 556 multiprobe system is used to determine pH,conductivity.

In literature several formulas for chlorophyll concentration are available (UNESCO 1966,
Stickland and Parsons 1968, Jeffrey and Humphrey 1975).


Chlorophyll (spectrophotometric analysis)

Sampling

Water samples collected for chlorophyll analysis from the field filtered through
0.45micrometer filter. Filtering and then handling of filters performed under dimmed
lighting. After filtering, placed in a cryo-tube. We labeled each tube with cruise number,
station number, depth and pigment number. The excess moisture in the filters removed
before freezing. +Analysis


All glassware rinsed three times with MQ water and once with acetone (AR). Frozen filters
are cut into halves and placed in a clean 10 ml centrifuge tube. 3 ml of 100% acetone is
added to the tube. Cover tube with parafilm and vortex for 30 seconds before placing the
tube in an ice-water bath whilst the filter and acetone are sonicated for 15 minutes. The
filter and acetone are then stored for at least 18 hours at 4°C. After this time, 0.2 ml MQ
water is added to each tube (solvent » 90:10 acetone : water) and the filter and solvent
sonicated for another 15 minutes. Solvent and filter are then transferred quantitatively to a
Biorad column (see figure x) containing a small GF/F filter acting as a plug. The sample tubes
are rinsed with 2 x 0.5 ml of acetone/water (90:10) which is quantitatively added to the
Biorad column. Each Biorad column is fitted into a centriguge tube and centrifuged for 5
minutes at 5000 rpm. The filtrate is stored in the cool and dark . The absorbance of the
filtrate is measured using a U.V./visible spectrophotometer with 10 mm path length optical
glass cells. Absorbance is read at wavelengths of 750, 664, 647 and 630 nm.




ACKNOWLEDGEMENT 2-

Dangers with phosphate

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If there is too less phosphate in the aquarium water very sensitive animals like Tridacna or
Acropora will stop growing and in the worst case they will die. If there is too much
phosphate in the water animals will die, too. The optimum concentration for sea water
aquaria is between 0,05 to 0,20 mg/l (ppm) phosphate. But in this interval even good
aquaristic tests are not sensible. So it is better to take a water sample two times per year
and go to a lab or a good marine animal shop to control the phosphate concentration. For
big aquaria a photometer is a good instrument to control the water values.

Phosphate concentrations above 0,20 mg/l are able to destroy the sensible biological
balance in the aquarium. Too much phosphate causes a strong growth of green and blue
green algae. These algaes are able to grow on the animals and kill them. Even the algae in
corals - called zooxanthella - will grow very fast and the corals gets problems. The animal
takes out the algae and the animal bleaches. Bleached corals are extremely sensitive and will
decease very fast.

Nitrate-nitrite concentration- Nitrates are a form of nitrogen, which is found in several
different forms in aquatic ecosystems. These forms of nitrogen include ammonia (NH3),
nitrates (NO3), and nitrites (NO2). Nitrates are essential plant nutrients, but in excess
amounts they can cause significant water quality problems. Together with phosphorus,
nitrates in excess amounts can accelerate eutrophication, causing dramatic increases in
aquatic plant growth and changes in the types of plants and animals that live in the stream.
This, in turn, affects dissolved oxygen, temperature, and other indicators. Excess nitrates can
cause hypoxia (low levels of dissolved oxygen). The natural level of ammonia or nitrate in
surface water is typically low (less than 1 mg/L); in the effluent of wastewater treatment
plants, it can range up to 30 mg/L.

As a result, nitrates serve as a better indicator of the possibility of a source of sewage .

Water that is polluted with nitrogen-rich organic matter might show low nitrates.
Decomposition of the organic matter lowers the dissolved oxygen level, which in turn slows
the rate at which ammonia is oxidized to nitrite (NO2) and then to nitrate (NO3). Under such
circumstances, it might be necessary to also monitor for nitrites or ammonia, which are
considerably more toxic to aquatic life than nitrate. The more commonly used cadmium
reduction method produces a color reaction that is then measured either by comparison to a
color wheel or by use of a spectrophotometer.

Cadmium Reduction Method

The cadmium reduction method is a colorimetric method that involves contact of the nitrate
in the sample with cadmium particles, which cause nitrates to be converted to nitrites. The
nitrites then react with another reagent to form a red color whose intensity is proportional
to the original amount of nitrate. The red color is then measured either by comparison to a
color wheel with a scale in milligrams per liter that increases with the increase in color hue,
or by use of an electronic spectrophotometer that measures the amount of light absorbed
by the treated sample at a 543-nanometer wavelength. The absorbance value is then
converted to the equivalent concentration of nitrate by using a standard curve. Methods for
making standard solutions and standard curves are presented at the end of this section.


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Results and Discussion




                         13
Findings

Table 1Environmental parameters of 3 stations.
                       0
Station    Temperature( C)   Salinity(ppt)   DO(mg/l)      BOD(mg/l)   S.Solids(gr)   Kl-       Secchi
                                                                                      a(μg/l)   Disk

1-S        11,0              11,67           6,25          2,96        0,0118         0,970     0,5
1-5        11,5              17,61           7,05          0,56        0,0116         0,410
2-S        11,0              16,40           9,02          1,20        0,0107         1,950
2-5        11,0              15,96           10,57         2,33        0,0114         0,880
                                                                                                1,7
2-10       11,0              18,05           8,92          1,47        0,0077         1,100
2-20       12,0              21,02           6,80          2,02        0,0103         0,780
2-30       15,5              32,57           5,74          0,58        0,0147         0,320
3-S        11,0              17,61           7,68          1,06        0,0089         1,700
3-5        11,0              16,84           7,01          3,51        0,0088         1,700
                                                                                                8,5
3-10       11,0              16,07           10,30         1,50        0,0082         1,580
3-20       11,5              19,92           11,77         2,82        0,0103         0,780
3-30       15,5              30,26           6,67          4,22        0,0151         0,430


Table 2-Nutrient salt value of the 3 station.


Station     Nitrate and       Ammonium          Silicate      Phosphate
            Nitrite
1-S         11,58             1,43              23,26         4,16
1-5         4,00              1,82              6,98          3,37
2-S         2,86              2,43              9,30          1,71
2-5         1,34              1,23              6,98          1,16
2-10        1,01              1,33              4,65          0,92
2-20        0,72              1,02              4,65          1,22
2-30        4,07              0,87              4,65          3,43
3-S         0,27              0,66              2,33          0,98

                                                                                                         14
3-5          0,20                0,46   2,33   0,73
3-10         0,16                2,15   4,65   1,41
3-20         0,60                1,80   4,65   0,80
3-30         2,55                1,52   4,65   1,59




Diagram1. Sıcaklık=temperature

Tuzluluk=Salinity,

Çözünmüş oksijen =Dissolved oxygen

klorfil a =chloropyll a

istasyon-station

derinlik-depth




Dıagraml 2. Depth-derinlik

Nitrat-nitrit=Nitrate-nitirte

Amonyum- Ammonium


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Fosfat-phosphate

Silikat- Silicate




Dıagram 3.

BOİ=Biological oxygen demand

OİP _oxydation potentiial(OP)

İletkenlik_conductivity ,TÇK: total dissolved solids




Diagram 4. Askıda katı madde=Suspended solids

Toplam çözünmüş katı madde-Total dissolved solids(TDS)

    STATION           pH               OP         CUNDUCTIVITY    TDS
                                       mV            mS/cm         g/l
      1-Y             7.90             118           18.725      16.456
       1-5            7.99             128           23.866      20.888
      2-Y             8.04             107           20.645      18.259
       2-5            8.10             111           21.307      18.785
      2-10            8.10             115           22.077      19.374
      2-20            8.04             122           27.722      23.808
      2-30            7.78             135           39.995      32.159
      3-Y             8.06             112           21.292      18.738


                                                                          16
                            3-5                      8.04                 116                       21.358                  18.778
                           3-10                      8.02                 119                       22.134                  19.339
                                                                                    Nitrate-        Ammonium                                                            Conductivi
                                                                                    nitirte                                     phosphate                               ty


                  Temperature     Salinity           DO      BOD     chloropyll a                                Silicate                     pH           OP                             TÇK   AKM
Temperature

Salinity                   **
                    ,841
DO                  -,470            -,354
BOD                 -,023            -,133           -,049
chloropyll a               **                *
                   -,855             -,596           ,386    ,084
Nitrate-nitirte      ,317             ,046           -,510 -,203       -,477

Ammonium            -,023            -,231           ,406    -,105     ,000           ,196

Silicate                                                                                       **            *
                    -,101            -,462           ,034    -,082     -,139         ,731             ,611
phosphate                                                                                      **                           *
                     ,294            -,070           -,538 -,301       -,382         ,804             ,371         ,671

pH                         **                                                *
                   -,792             -,436           ,513    -,206    ,617            -,439           -,243        -,106          -,503
OP                         **                *                               **                                                                       **
                    ,869             ,680            -,441   ,140    -,814            ,175            ,070         -,161           ,259       -,874
Conductivity               **                **                              **                                                                                    **
                    ,881             ,844            -,210 -,028     -,775            -,014           -,014        -,334           ,007        -,572        ,867
TÇK                        **                **                              **                                                                                    **           **
                    ,881             ,858            -,182 -,056     -,814            ,056            -,021        -,274           ,007        -,503        ,825         ,986
AKM                        *                                                  *                **                                        **           *
                    ,594              ,204           -,532   ,070     -,640          ,802             ,116         ,492           ,722        -,700             ,462      ,256        ,284
                           3-20                      7.90                 130                       28.015                  24.062
                           3-30                      7.66                 168                       33.871                  27.775
                  Correlation coefficient r
                                      The correlation coefficient r is a measure of the linear relationship between two attributes or
                                      columns of data. The correlation coefficient is also known as the Pearson product-moment
                                      correlation coefficient. The value of r can range from -1 to +1 and is independent of the units of
                                      measurement. A value of r near 0 indicates little correlation between attributes; a value near +1
                                      or -1 indicates a high level of correlation.

                                      When two attributes have a positive correlation coefficient, an increase in the value of one
                                      attribute indicates a likely increase in the value of the second attribute. A correlation coefficient
                                      of less than 0 indicates a negative correlation. That is, when one attribute shows an increase in
                                      value, the other attribute tends to show a decrease.

                                      Consider two variables x and y:

                                                    If r = 1, then x and y are perfectly positively correlated. The possible values of x and y
                                                     all lie on a straight line with a positive slope in the (x,y) plane.
                                                    If r = 0, then x and y are not correlated. They do not have an apparent linear
                                                     relationship. However, this does not mean that x and y are statistically independent.
                                                    If r = -1, then x and y are perfectly negatively correlated. The possible values of x and
                                                     y all lie on a straight line with a negative slope in the (x,y) plane.




                  Phytoplankton species



                                                                                                                                                                                     17
                                                         Stations
Species
                                                         1          2   3

DİNOPHYCEAE

Neoceratium furca (Ehrenberg) F.Gomez, D.Moreira &
                                                   +                +   +
P.Lopez-Garcia, 2009

Neoceratium fusus (Ehrenberg) F.Gomez, D.Moreira &
                                                   +                +   +
P.Lopez-Garcia, 2009

Neoceratium longirostrum (Gourret) F.Gomez, D.Moreira &
                                                        +           -   -
P.Lopez-Garcia, 2009

Neoceratium trichoceros (Ehrenberg) F.Gomez, D.Moreira
                                                       +            +   +
& P.Lopez-Garcia, 2009

Neoceratium tripos (O.F.Müller) F.Gomez, D.Moreira &
                                                     +              -   +
P.Lopez-Garcia 2010

Dinophysis acuta Ehrenberg, 1841                         +          +   -

Dinophysis caudata Saville-Kent, 1881                    +          +   +

Dinophysis fortii Pavillard, 1923                        +          +   -

Diplopsalis sp Bergh, 1881                               +          -   +

Noctiluca scintillans (Macartney) Kofoid & Swezy, 1921   +          +   +

Oxytoxum scolopax Stein, 1883                            +          -   -

Dinophysis rotundata Claparède & Lachmann, 1859          +          +   +

Prorocentrum compressum (Bailey, 1850) Abé ex Dodge,
                                                     +              -   -
1975

Prorocentrum micans Ehrenberg, 1833                      +          +   +

Prorocentrum scutellum Schröder, 1900                    +          -   -

Protoperidinium conicum (Gran, 1900) Balech, 1974        +          +   +

Protoperidinium depressum (Bailey, 1850) Balech, 1974    +          +   +

Protoperidinium divergens (Ehrenberg) Balech, 1974       +          +   +

Protoperidinium oceanicum (VanHöffen, 1897) Balech, +               -   -


                                                                            18
1974

Protoperidinium pellucidum Bergh, 1882                   +    +   +

Protoperidinium steinii (Jörgensen, 1899) Balech, 1974   +    +   +



DİCTYOPHYCEAE

Dictyocha fibula Ehrenberg, 1837                         -    +   -

Dictyocha speculum Ehrenberg, 1837                       +    +   -



BACİLLARİOPHYCEAE

Achnanthes longipes C.Agardh, 1824                       +    -   -

Chaetoceros curvisetus P.T. Cleve, 1889                  +    +   +

Chaetoceros danicus Cleve, 1889                          +    +   +

Chaetoceros decipiens Cleve, 1873                        +    +   +

Chaetoceros diadema (Ehrenberg) Gran, 1897               -    +   +

Chaetoceros didymus Ehrenberg, 1845                      +    +   +

Chaetoceros laciniosus Schütt, 1895                      +    +   -

Chaetoceros socialis H.S.Lauder, 1864                    -    +   -

Coscinodiscus perforatus Ehrenberg, 1844                 -    +   +

Coscinodiscus radiatus Ehrenberg, 1840                   +    +   -

Ditylum brightwellii (T.West) Grunow, 1885               +    +   +

Guinardia flaccida (Castracane) Peragallo, 1892          +    -   +

Navicula sp Bory de Saint-Vincent, 1822                  +    -   -

Pleurosigma macrum W.Smith 1853:                         +    -   -

Proboscia alata (Brightwell) Sundström, 1986             +    +   +

Pseudo-nitzschia delicatissima (P.T. Cleve, 1897) Heiden,
                                                          +   +   -
1928


                                                                      19
Pseudo-nitzschia pungens (Grunow ex P.T. Cleve, 1897)
                                                      -                 +   -
Hasle, 1993

Pseudosolenia calcar-avis (Schultze) Sundström, 1986        +           +   +

Rhizosolenia setigera Brightwell, 1858                      +           +   +

Skeletonema costatum (Greville) Cleve, 1873                 +           +   +

Striatella unipunctata (Lyngbye) C. Agardh, 1830            -           +   -

Thalassionema nitzschioides (Grunow) Mereschkowsky,
                                                    +                   +   +
1902

Thalassiosira rotula Meunier, 1910                          +           +   +



Macro-Bentic Fauna species

                                                       STATIONS
Species
                                                       1        2   3

ANTHOZOA

Diadumene lineata (Verrill, 1869)                      -        -   +

POLYCHAETA

Alitta succinea (Leuckart, 1847)                       +        -   +

Capitella telata Blake, Grassle, Eckelbarger, 2009     +        -   -

Ficopomatus enigmaticus (Fauvel, 1923)                 +        -   -

Harmothoe cf. imbricata (Linnaeus, 1767)               +        -   -

Heteromastus filiformis (Claparède, 1864)              +        -   -

Malacoceros fuliginosus (Claparède, 1870)              -        +   +

Polydora cornuta Bosc, 1802                            +        -   +

Prionospio sp.                                         +        -   -

Spirobranchus triqueter (Linnaeus, 1758)               +        -   -

Streblospio gynobranchiata Rice & Levin, 1998          -        -   +



                                                                                20
AMPHIPODA

Echinogammarus olivii (Milne-Edwards, 1830)   +   -   +

Microdeutopus gryllotalpa Costa, 1853         +   -   -

GASTROPODA

Ecrobia ventrosa (Montagu, 1803)              +   +   -

Cyclope neritea (Linnaeus, 1758)              -   +   -

Nassarius reticulatus (Linnaeus, 1758)        +   +   -

Pusillina inconspicua (Alder, 1844)           +   -   -

BIVALVIA

Abra alba (W. Wood, 1802)                     -   +   -

Cerastoderma glaucum (Bruguière, 1789)        +

Corbula gibba (Olivi, 1792)                   -   -   +

Mytilus galloprovincialis Lamarck, 1819       +   -   +




                                                          21
Acknowledgements
We are grateful to the scientists İstanbul University for their efforts.



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                                                                                     22
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